overview
The Multimodal Vision Research Lab conducts fundamental and applied
research that is grounded in computer vision. We simultaneously focus
on publishing in top-ranked computer vision venues (e.g., CVPR, ICCV,
and ECCV) and working closely with domain experts to solve problems in
a broad range of disciplines, including medical imaging, transportation
engineering, and astrophysics.
We have a
supportive culture where people can do impactful research, learn new
skills, and achieve their personal goals.
While most of our members have computer science (CS) backgrounds
and/or are working on CS degrees, we encourage people with strong
computational and quantitative skills from other disciplines to apply,
including, but not limited to, Electrical Engineering, Physics,
Mathematics, Statistics, and Data Science. Lab members primarily
focus on implementing computer vision algorithms using Python and
Pytorch. In addition, most of our projects involve some aspects of
machine learning, image/signal processing, linear/nonlinear
optimization, and large-scale data processing.
current openings (updated Mar 10, 2021)
We have several active openings for graduate and postdoctoral
researchers (starting in Summer and Fall 2021). Topics include:
- image geo-localization of ground-level imagery
- object tracking in video
- change detection in satellite imagery
In all cases, the focus will be on developing image-understanding
systems using deep-learning techniques. These projects are
collaborative with industrial partners and require US
citizenship or permanent resident status.
General information and expectations for each type of position:
- Postdoctoral scholars will work closely with the lab
director to develop a research program that is aligned with the
funding source and their personal interests and abilities. In addition
to working on research problems, they will supervise
graduate/undergraduate researchers, help with proposal development,
and take a leading role in project management. They must have a PhD
and have prior experience in publishing original research, ideally in
top-tier computer science venues. Please see the Office of Postdoctoral Affairs
for additional information about benefits offered to postdocs by the
University of Kentucky.
- Graduate students initially focus on implementing
state-of-the-art image understanding systems, and then developing an
original research program. We offer both fully funded research
assistantships (stipend + health + tuition) and hourly positions. We
also occasionaly support unfunded research as part of an independent
research class (CS 612).
- Undergraduate researchers will focus on implementing
state-of-the-art image understanding systems in close collaboration
with a graduate student or a postdoc. We primarily offer paid
positions, but occasionaly offer unfunded research positions as part
of an independent research class (CS 395). We are especially
interested in students that are likely to stay for a master's
degree.
qualifications
We look holistically at each applicant to determine if they are a good
fit for our current and future needs. We generally look for
new members with the following qualifications:
- [required] strong programming skills (we implement primarily in
Python, but knowledge of Python is not required)
- [required] strong grades in math and statistics courses (minimum
GPA: 3.5 for undergraduate researchers)
- [required] strong English oral and written communications skills
- [ideal] ability to build basic systems using machine learning and/or
mathematical optimization
- [helpful] experience with deep learning and/or computer vision
- [helpful] ability to build large-scale data processing systems using Linux tools
- [helpful] prior research experience
applying
The following documents should be sent to the lab director,
Dr. Nathan Jacobs:
- resume/CV
- a brief research statement (what are you interested in working on and why is it important?)
- transcript(s)
- one or more recommendation letter(s), which should be sent
directly by the writer
In addition, be sure to include the type of position you are
interested in (postdoc, graduate, or undergraduate), your funding
situation, when you are available to start, and anything else you
think might be helpful.